Agricultural work machine

ABSTRACT

An agricultural work machine, in particular a harvester, has a header for performing agricultural work and having a control device which has at least one sensor unit for detecting a crop stream in and/or around the header and an image processing unit for processing images which are generated by the sensor unit based on the crop stream detected via sensor. The control device is configured to detect regions of like characteristics, components of the header and properties of the crop stream and is configured to use that which has been detected for open loop control and/or closed loop control of process sequences in the agricultural work machine.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 USC 119 of German ApplicationNo. DE 102018121031.0 filed on Aug. 29, 2018, the disclosure of which isherein incorporated by reference.

BACKGROUND OF THE INVENTION

The invention is directed to an agricultural work machine and to amethod for operating an agricultural work machine.

Agricultural work machines which include, in particular, self-propelledharvesters such as combine harvesters and chopper-type forage harvestersgenerally have, as a header, a crop collection arrangement by whichcrops in the field stand can be cut and collected for further processingin the combine harvester. A crop collection arrangement in itselfgenerally has a plurality of individual components which can be operatedwith different parameters. Examples of such components in a combineharvester are a crop pickup device in the form of a reel, a crop cuttingdevice in the form of a cutting unit table with a knife bar, a cropconveying device in the form of a conveyor screw, in particular a crossauger, and a crop intake device in the form of an inclined conveyor. Ina combine harvester, the placement (cut height, position) and rate ofrotation of the reel and the speed of the cross auger and of theinclined conveyor, for example, can be adjusted. The crop stream insidethe crop collection arrangement can be influenced in this way. Thedriving speed of the harvester further influences the crop stream insideof the crop collection arrangement because the amount of collected cropwhich is processed by the crop collection arrangement is influenced inthis way.

Despite a number of automatic adjustments of the crop collectionarrangement, the driver of the agricultural work machine must constantlymonitor the crop stream inside of the crop collection arrangement aswell as inside of the combine harvester. For example, the driver mustensure that the produce flow velocity inside of the header and in therest of the interior of the combine harvester is as uniform as possiblebecause when the produce flow is irregular the speed of the vehicle and,therefore, collection of crops may have to be reduced in order to avoida crop jam. If a crop jam occurs, the harvesting process must beinterrupted and a time-consuming clearing of the crop jam must beperformed in the header and, further, in the combine harvester. The timerequired for this significantly impairs the efficiency of the harvestingoperation.

Therefore, it is desired that an open loop control and/or closed loopcontrol of the process sequences in the agricultural work machine, forexample, in the combine harvester, is automated as far as possible so asto relieve the burden from the driver. This requires an analysis of theprocess sequences which is as differentiated as possible beginning withthe process sequences inside of the header. For an optimal analysis, itis necessary to monitor the crop stream in an optimal manner and todetect changes in the crop stream, particularly the produce velocity, aspromptly as possible and to carry out corresponding control steps.

To this end, it is known, for example, from EP 3 300 019 A1, to providea control device with a sensor unit and an image processing unit viawhich the crop stream is monitored using the method of optical flow. Thesensor device has, for example, two cameras which are directed from thedriver's cab onto the crop collection arrangement and which encompassindividual portions of the components and the crop stream. The sensordevice generates an image sequence, i.e., a plurality of consecutiveimages. According to the prior art, every two consecutive images aregrouped to form an image pair, and positional displacements of intensitypatterns, that is, of pixels or groups of pixels, between the images ofthe respective image pair are determined. The intensity patterns are notnecessarily formed by objects or particular crop features but generallyby pixels or groups of pixels in the image whose position changes fromone image to the next image. When the time interval between the imagesof the image pair is known, the velocity at which the intensity patternstravel can be inferred from these positional displacements of theintensity patterns. The velocities of a plurality of intensity patternscan be combined for each image pair and each image sequence comprising aplurality of image pairs to form velocity characteristic maps. Avelocity characteristic map of this kind relates to optical flow. Withregard to the method of optical flow and its application for monitoringthe crop stream inside of a header, reference is made to EP 3 300 019 A1which originated with the Applicant and the disclosure of which isincorporated by reference into this application.

One challenge consists in considering and analyzing the crop stream inthe most differentiated manner possible in order to respond to anincipient crop jam in a timely manner.

The problem upon which the invention is based is to configure andfurther develop an agricultural work machine in such a way that themonitoring of a header is further improved with respect to accuracy,reliability and timeliness.

SUMMARY OF THE INVENTION

The above-stated problem is solved in an agricultural work machine suchas a harvester, having a header for performing agricultural work andhaving a control device which has at least one sensor unit for detectinga crop stream in and/or around the header and an image processing unitfor processing images which are generated by the sensor unit based onthe crop stream detected via sensor. The control device is configured todetect regions of like characteristics, components of the header andproperties of the crop stream and is configured to use that which hasbeen detected for open loop control and/or closed loop control ofprocess sequences in the agricultural work machine.

A key basic consideration consists in detecting the header, inparticular a crop collection arrangement of a combine harvester orchopper-type forage harvester, using sensors such that individual areasin the header and around the header can be detected, i.e., identified.The areas are, for one, regions of like characteristics. A region oflike characteristics is, for example, the unharvested field stand infront of the header in driving direction. A further region of likecharacteristics is, for example, the harvested field stand (stubblefield) behind the header.

Regions of like characteristics may also include produce flow regions oflike characteristics. For example, a region of like characteristics isformed by the crop stream within the crop pickup device, in particularthe reel, and another region of like characteristics is formed by thecrop stream vertically above the crop cutting device, particularlyvertically above the cutter unit table, in particular in the areabetween the crop pickup device or reel and the crop conveying device, inparticular the conveyer screw.

Apart from these areas which are characterized by the presence of mainlybiomass (crop, field stand) within the area, further areas arecomponents of the header having a surface portion of a machine part ofthe component, which surface portion can be detected by the sensor unit.Corresponding components are, for example, the crop pickup device,particularly the reel, the crop cutting device, particularly the cutterunit table, the crop conveying device, particularly the conveyer screw,and/or the crop intake device, particularly the inclined conveyor, of acrop collection arrangement, for example, of a combine harvester.Accordingly, each of these areas is defined by the presence of a surfaceportion of a machine part of a component of the header.

In addition to these areas, it is suggested that a detection ofproperties of the crop stream, for example, produce flow velocities ofthe crop stream or portions thereof and/or a crop jam, is carried out.

On the basis of the information gathered in an analysis process of thistype, process sequences in the agricultural work machine are thencontrolled according to the suggestion in a subsequent or simultaneouslyrunning open loop control process and/or closed loop control process. Asa result of dividing into regions and components, the behavior of aheader and of the crop stream guided along therein can be considered andanalyzed in a particularly differentiated manner. Correspondingly, themonitoring of a header, in particular a crop collection arrangement, isfurther improved with respect to accuracy, reliability and timeliness.

It is provided according to the suggestion that the control device isconfigured to detect regions of like characteristics, components of theheader and properties of the crop stream and is configured to use thatwhich has been detected, i.e., the detected regions of likecharacteristics, the detected components of the header and/or thedetected properties of the crop stream, for open loop control and/orclosed loop control of process sequences in the agricultural workmachine.

“Detection” of the above-mentioned regions and components preferablydoes not simply mean a determination of areas but also an unambiguousidentification of the respective area, that is, an association of thearea with a function and/or property. Accordingly, for example,detection of the region with the field stand in front of the headermeans that an area is first detected or located by sensor detection andimage processing and this area is then identified as a specific areawith a particular function and/or property, for example, specifically asfield stand in front of the header. Therefore, the individual areas canbe distinguished from one another not only based on their position butalso based on their function and/or property. This makes it possible todifferentiate determined motions.

In one embodiment, an identification is possible based on storedidentification data characterizing the respective area (region orcomponent). For example, determined dimensions or positions of a regionor component inside of the header or outside of the header can be storedin a data storage as identification data, and the region or componentcan then be identified as a determined region or component on the basisof these identification data.

In order to allow the determination of regions and/or components and/orproduce stream properties, the image processing unit can use variousmethods based on the images generated by the sensor unit. For example,the image processing unit can use the method of velocity characteristicmap determination, also known as optical flow method, which will beexplained in more detail later. Additionally or alternatively, it canuse the method of line detection which will also be explained later.Additionally or alternatively, it can also use at least one colorfilter. In this way, an object detection in which, in particular,biomass is distinguished from mechanical objects can also be carriedout.

A velocity characteristic map determination, or optical flow method, isan image processing method, know per se, and is based on thedetermination and analysis of intensity patterns (pixels or pixelgroups) in consecutive images of an image sequence. Accordingly, animage sequence, i.e., a plurality of consecutive images, is generatedparticularly via one or more cameras. Every two consecutive images, inparticular two directly successive images, of the image sequence aregrouped to form an image pair, and positional displacements of intensitypatterns, i.e., of pixels or groups of pixels, between the images of therespective image pair are determined. When the time interval between theimages of the image pair is known, the velocity at which the intensitypatterns travel can be inferred from these positional displacements ofthe intensity patterns. The direction in which the intensity patternstravel can also be determined from the positional displacements. Theoptical flow method accordingly comprises the pixel-based generation ofinformation on velocities of intensity patterns on the one hand and onthe movement directions of these intensity patterns on the other hand.The velocities of a plurality of intensity patterns can be combined foreach image pair and each image sequence comprising a plurality of imagepairs to form velocity characteristic maps, which can also be referredto broadly as optical flow.

Since the biomass on the one hand and the surface portions of themechanical components of the header on the other hand move,respectively, in a characteristic manner, the image processing unit canalso distinguish the individual areas from one another.

A method of line detection can be used additionally or alternatively.This is an image processing method in which an edge detection isinitially carried out for the respective image and an edge image isgenerated therefrom. In an edge detection, two-dimensional areas in adigital image are separated from one another when they differ from oneanother sufficiently with respect to color value or grayscale value,brightness or texture along straight or curved lines. An edge detectionof this kind and generation of an edge image are carried out inparticular by means of the Canny algorithm, known per se. In the methodof line detection, according to the suggestion, straight lines aresubsequently determined and displayed or highlighted in the edge imageby means of a straight line detection. A straight line detection of thiskind is preferably carried out by means of the Hough transform, knownper se. Contours of components or of machine parts thereof can bedetected by means of the line detection, which likewise allowsindividual areas (regions or components) to be distinguished from oneanother and possibly also identified. In this way, in a digital imageshowing, for example, a crop collection arrangement of a combineharvester, the reel in particular can be emphasized and accordinglyidentified because it is shown by many straight lines in atwo-dimensional image. Also, apart from the detection of the respectivecomponent, it is possible to determine geometric parameters of therespective component, for example, the inclination and/or height of thecomponent.

When image pairs of consecutive images of an image sequence generated bythe sensor unit are processed using line detection, image line patterns,namely, patterns of the straight line or lines determined by means ofstraight line detection, result in every image. In a corresponding imagepair, positional displacements of line patterns, that is, of lines orline groups, between the images of the respective image pair can then bedetermined similarly as in the method of velocity characteristic mapdetermination. When the time interval between the images of the imagepair is known, the velocity at which the line patterns travel can alsobe inferred from these positional displacements of line patterns. Inprinciple, the direction in which the line patterns move can also bedetermined. That is, the line detection comprises line-based generationof information on velocities of line patterns and possibly also onmovement directions of the latter. Therefore, in addition to thedetection of the areas, it is also possible to determine the velocity atwhich lines or contours of components move between two consecutiveimages.

The method of the invention also includes determining reference regionsor reference surface portions with which another region to be analyzedcurrently can be compared. A comparison of this type between tworegions, one of which serves as basis (reference), makes it possible toinfer properties, particularly the velocity, in the region to becurrently analyzed. This holds true not only for regions but also forcomponents and surface portions thereof. In a particularly preferredmanner, there is the possibility of determining a reference velocity fora reference region. The reference velocity can be determined, forexample, by relating the driving speed of the agricultural work machine,which is known or can be accurately detected by appropriate sensors, toa velocity of the field stand of a region, which velocity is calculatedfrom the displacement amounts. The reference velocity is a velocitycorresponding to the driving speed in a determined ratio. This is alsocorrespondingly possible for velocities of surface portions of machineparts of the components. In this case, for example, the rate of rotationof a component, for example, the reel, which is known or can beaccurately detected by appropriate sensors, can be correlated to thevelocity of the surface portion calculated from the displacementamounts. The reference velocity is then a velocity corresponding to therate of rotation in a determined ratio. Velocities in other regions orof other surface portions of components can then also be inferred basedon reference velocities of this kind.

According to one embodiment, the header is a crop collection arrangementfor cutting and picking up crop from a field stand which has, ascomponents, a crop pickup device, a crop cutting device, a cropconveying device and a crop intake device. In particular, it is a cropcollection arrangement of a combine harvester or chopper-type forageharvester.

In the further configuration, the velocity of a surface portion of amachine part of the respective component can also be determined on thebasis of a marker which then forms the surface portion. Either acharacteristic location, for example, edge or surface area, on therespective machine part or a separately applied marking serves asmarker. The marker then shows the surface portion that is detected bythe sensor unit for determining the velocity.

In a preferred configuration, different sensors for detecting the cropstream and/or header can be provided, in particular at least one opticalsensor, for example, a camera or a plurality of cameras. An opticalsensor of this kind is useful particularly when the method of velocitycharacteristic map determination (optical flow method) is to be used. Inprinciple, the sensor unit can also have at least one Lidar sensor, atleast one radar sensor and/or at least one ultrasound sensor. All of thesensors mentioned above are also suitable for use with the method ofline detection.

According to a further teaching a method is claimed for the operation ofan agricultural work machine, in particular an agricultural work machineas suggested above, in which regions of like characteristics, componentsof the header and properties of the crop stream are detected, andprocess sequences in the agricultural work machine which are based onthe latter are controlled by open loop controlling and/or closed loopcontrolling.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described in more detail in the followingreferring to drawings in which only one embodiment example is depicted.The drawings show:

FIG. 1 a schematic side view of a suggested agricultural work machineand a detailed view of the header of the agricultural work machine;

FIG. 2 a schematic front view of the suggested agricultural work machinewith the header;

FIG. 3 a schematic view a) of an image with the header that is generatedby the sensor unit of the suggested agricultural work machine, and b) ofthe image after processing by the image processing unit by means of afirst image processing method; and

FIG. 4 a schematic view of an image generated by the sensor unit of thesuggested agricultural work machine with the header a) after a firstprocessing step of a second image processing method and b) after asecond processing step of the second image processing method.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The suggested agricultural work machine 1 which in this case is acombine harvester, for example, has as header 2 a crop collectionarrangement which is formed in this case by a cutting unit 3 and isarranged in front of the agricultural work machine 1 in drivingdirection. The crop collection arrangement 2 and cutting unit 3 serverespectively to cut and collect crop 4 from a field stand 5, and thecrop 4 is supplied for further processing by a plurality of further workelements 6 of the agricultural work machine 1. The further comments withregard to the example of the crop collection arrangement 2 are notlimited to this case of application but also apply in a correspondingsense for other headers 2, for example, a crop header of a chopper-typeforage harvester.

In this instance and preferably, the crop collection arrangement 2 hasin every case as components C, D, E, F a crop pickup device 7 in theform of a reel, a crop cutting device 8 in the form of a cutting unittable with a knife bar, a crop conveying device 9 in the form of aconveyor screw, in particular a cross auger, arranged downstream thereofwith respect to the process, and a crop intake device 10 in the form ofan inclined conveyor which is again arranged downstream thereof withrespect to the process.

In the suggested agricultural work machine 1, the crop 4 is guided ascrop stream (indicated by arrows in FIGS. 1 and 3 a)) through the cropcollection arrangement 2. In this instance and preferably, the crop 4 iscollected and held via the crop pickup device 7 or reel while it isbeing cut by the crop cutting device 8. The cut crop 4 is then movedtoward the crop conveying device 9 which, in this instance andpreferably, extends transversely and is conveyed from the latter intransverse direction, i.e., transverse to driving direction, toward thecenter of the vehicle where it is then taken in by the crop intakedevice 10 and conveyed further into the interior of the agriculturalwork machine 1.

The agricultural work machine 1 further has a control device 11 which,in addition to the above-mentioned components C, D, E, F of the cropcollection arrangement 2, also serves in this instance and preferably tocontrol the further work elements 6 of the agricultural work machine 1.The controlling can include speed controls and/or height adjustmentsand/or position adjustments. Also, in this instance and preferably, thedriving speed of the agricultural work machine 1 is controlled via thecontrol device 11. In this instance and preferably, control device 11has a sensor unit 12 in the form of two cameras. Sensor unit 12 isarranged in the front area of the agricultural work machine 1,particularly on and/or inside of the driver's cab of the agriculturalwork machine 1, and serves for optical detection of the crop stream. Therange of optical detection is represented by dashed lines in FIGS. 1 and2.

Further, the control device 11 has an image processing unit 13 forprocessing images 14, one of which is shown by way of example in FIG. 3a). Images 14 are generated by the sensor unit 12 based on the opticallydetected crop stream.

Further, in this instance and preferably, the control device 11 has adata output unit 15 which in particular comprises a display device 15 aand serves for optional output or display of the images 14 processed bythe image processing unit 13.

It is key, for one, that the control device 11 is configured to detectregions A, B, G, H of like characteristics, components C, D, E, F of theheader 2 or, in this case, of the crop collection arrangement andproperties of the crop stream. The regions A, B, G, H of likecharacteristics on the one hand and components C, D, E, F of header 2 onthe other hand constitute areas in and around the header 2 which aredetectable by the sensor unit 12 and which are particularly suitable asbasis for a differentiated consideration and analysis of the cropstream.

In the preferred embodiment example of the unharvested field stand 5shown in the drawing, a region A of like characteristics is in front ofthe crop collection arrangement 2 with respect to driving direction. Inthis instance, a further region B of like characteristics is theharvested field stand 5 in the form of the stubble field behind the cropcollection arrangement 2. Yet another region G of like characteristicsis formed by the crop stream within the crop pickup device 7 in the formof the reel. Finally, yet another region H of like characteristics inthe embodiment example is formed by the crop stream vertically above thecrop cutting device 8 in the form of the cutting unit table, in thiscase in the area between the reel and the crop conveying device 9 in theform of the conveyor screw. All of these regions are characterized inthat biomass flows past them (in the form of the field stand whiledriving) or biomass flows through them (in the form of the crop stream).

In addition to these areas which are characterized by the presence ofmainly biomass (crop, field stand) within the area, further areas areformed by components C, D, E, F of the crop collection arrangement 2 inthe present embodiment example. These areas have in each instance atleast one surface portion of a machine part of the respective componentC, D, E, F, which surface portion can be detected by the sensor unit 12.Corresponding components C, D, E, F are, in this case, the crop pickupdevice 7 in the form of the reel, crop cutting device 8 in the form ofthe cutting unit table, crop conveying device 9 in the form of theconveyer screw and crop intake device 10 in the form of the inclinedconveyer. The list of suggested components is not meant to beconclusive. On the contrary, many other components which can likewise bedetected by sensors are conceivable, for example, also steps, frameparts or the like. Accordingly, each of these areas is defined by thepresence of a surface portion of a machine part of a component C, D, E,F of the crop collection arrangement 2.

Further, the control device 11 carries out the detection of propertiesof the crop stream, for example, of produce flow velocities of the cropstream or portions thereof, and/or a crop jam particularly via the imageprocessing unit 13.

Further, it is also key that the control device 11 uses that which isdetected, i.e., the detected regions and components A-H and the detectedproperties of the crop stream, for the open loop control and/or closedloop control of process sequences in the agricultural work machine 1. Onthis basis, parameters of components C, D, E, F of crop collectionarrangement 2 and/or parameters of further working elements 6 of theagricultural work machine 1, in the present instance, the combineharvester, can be adapted. Because of the division into regions andcomponents A-H, the crop collection arrangement 2 and the crop streamcan be considered and analyzed in a very differentiated manner, which inturn optimizes the crop collection arrangement 2 and the crop stream.

In the embodiment example shown here, the regions and components A-H arefirst detected or determined. Subsequently, at least some of the regionsand components A-H are specifically identified in that each of theseareas is compared preferably with associated identification data (e.g.,dimensions, positions, etc.) which characterize these areas and whichare stored particularly in the image processing unit 13. For example,the field stand 5 in front of the crop collection arrangement 2 can bedetermined as a region A and then also particularly identified as such,that is, as the field stand 5 in front of the crop arrangement 2.Correspondingly, the field stand 5 behind the crop collectionarrangement 2, for example, can be determined as a region B and thenidentified in particular specifically as the field stand 5 behind thecrop collection arrangement 2. In principle, this is also possible forcomponents. Accordingly, it is conceivable, for example, to determinethe crop pickup device 7 or reel as a component C and then tospecifically identify it as such, that is, as crop pickup device 7 orreel, or the crop cutting device 8 or cutting unit table can bedetermined as a component D and identified in particular as such. Otherexamples are also conceivable.

The determination of the regions and components A-H is carried out bymeans of the image processing unit 13, namely, by determining associatedimage areas 14 a-14 h in the images 14 generated by the sensor unit 12as will be explained in more detail later. To this end, different imageprocessing methods can be used individually or in combination. Twoparticularly preferred methods, namely, the method of velocitycharacteristic map determination and the method of line detection, aredescribed in more detail in the following. In principle, these methodscan also be combined with other methods for optimizing image data, forexample, by using at least one color filter, noise suppression, acontrast change, a change in brightness, or the like. An objectdetection which preferably comprises distinguishing biomass on the onehand and mechanical objects on the other hand and/or distinguishing oneor more regions A, B, G, H on the one hand and one or more surfaceportions of machine parts of components C, D, E, F on the other hand canthen be carried out by means of these methods.

The image processing unit 13 in the suggested agricultural work machine1 can produce a velocity characteristic map, also known as optical flow,based on the images 14 generated by the sensor unit 12, in this instanceand preferably by one or more cameras. The optical flow is the pixelmovement in the image area, also known as the flow field, determined byan image frequency. The image frequency is in turn defined by the pixelposition and the time. The movement is a vector field in an image 14that is generated by superimposing two images 14 of an image pair anddescribes the time-dependent displacement of a pixel or of a group ofpixels, also referred to hereinafter as intensity pattern, from oneimage 14 to the next image 14 of the image pair. The image which iscomposed of the two individual images 14 can be reworked beforehandthrough the image processing unit 13 as is described in detail, forexample, in EP 3 300 019 A1. The Lucas-Kanade method, in which the imageresolution of the images is reduced, is mentioned here merely by way ofexample. The resulting image is then used to produce the velocitycharacteristic map.

In this instance, the velocity characteristic map has, for one, theproduce flow velocities, particularly of crop particles, and velocitiesof surface portions of machine parts of components C, D, E, F of thecrop collection arrangement 2.

To produce the velocity characteristic map, the image processing unit 13groups two consecutive images 14 in each instance, in particular twodirectly successive images 14, of an image sequence generated by thesensor unit 12 to form an image pair. A time interval between the images14 of the respective image pair is detected by the image processing unit13. Additionally or alternatively, a time interval can be predeterminedby the image processing unit 13. Each image 14 of the respective imagepair has an intensity pattern, i.e., a pixel or a group of pixels. Theimage processing unit 13 determines positional displacements of theintensity patterns between the images 14 of the respective image pair,which positional displacements include displacement amounts anddisplacement directions. In this instance and preferably, thedisplacement amounts and displacement directions for each image pair arecombined as vectors of a vector field of the respective image pair.

Velocities are then calculated by the image processing unit 13 from thedisplacement amounts of the intensity patterns between the images 14 ofthe respective image pair and the time interval between the images 14 ofthe respective image pair. As has already been indicated, the velocitiesare produce flow velocities and/or velocities of surface portions ofcomponents C, D, E, F of the crop collection arrangement 2. Therespective velocity of a surface portion of a machine part of therespective component C, D, E, F can also be determined based on a markerwhich then forms the surface portion that is detected via sensor fordetermining the velocity of the surface portion of this component C, D,E, F.

A comparison of the velocities or displacement amounts and displacementdirections determined in the above-described manner makes it possible onthe one hand to divide into individual areas, i.e., the individualregions and components A-H, for example, because the velocities or thedisplacement amounts and displacement directions differ in all of theregions and components A-H. An exemplary division is shown in FIG. 3b ).

On the other hand, the above-mentioned detection of properties of thecrop stream, for example, the detection of an incipient crop jam, can becarried out based on the determined velocities or displacement amountsand displacement directions.

As is shown in FIG. 3b ), the images 14 generated by the sensor unit 12are divided by the image processing unit 13 into image areas whichcorrespond in each instance to one of the regions and components A-Hmentioned above. As can be seen from FIGS. 3a ) and 3 b), the sensorunit 12 detects the field stand 5 in front of and behind the cropcollection arrangement 2. In addition, in this instance and preferably,the crop pickup device 7, the crop cutting device 8, the crop conveyingdevice 9 and the crop intake device 10 are detected by the sensor unit12. The crop stream inside of the crop pickup device 7 and the cropstream vertically above the crop cutting device 8 are also detected, inthis case between the crop pickup device 7 and the crop conveying device9. In order to isolate the relevant areas with the crop stream, thedepicted image areas in the images 14 are determined as has beendescribed, in the present instance and preferably an image area 14 awith the field stand 5 in front of the crop collection arrangement 2, animage area 14 b with the field stand 5 behind the crop collectionarrangement 2, an image area 14 c with the crop pickup device 7, animage area 14 d with the crop cutting device 8, an image area 14 e withthe crop conveying device 9, an image area 14 f with the crop intakedevice 10, an image area 14 g with the crop stream inside of the croppickup device 7 and/or an image area 14 h with the crop streamvertically above the crop cutting device 8, in particular in the areabetween the crop pickup device 7 and the crop conveying device 9.

In principle, additionally or alternatively, individual image areas canalso be determined and/or highlighted through the method of linedetection, which is shown by way of example in FIG. 4 referring to thecrop pickup device 7 in the form of the reel.

Accordingly, in the embodiment example shown here, a plurality of images14 is also generated, in this case via the image processing unit 13 withthe method of line detection by the sensor unit 12, in this case also byone or more cameras. Alternatively or additionally, the sensor unit 12can have at least one Lidar sensor, radar sensor and/or ultrasoundsensor for detecting the crop collection arrangement 2. Based on theimages 14 generated in this way, an edge image is then initiallygenerated for the respective image 14, in this instance and preferablyby means of the Canny algorithm. Based on the latter, a straight linedetection is then carried out in which straight lines are determined inthe edge image, in this instance and preferably by means of the Houghtransform and, as is shown in FIG. 4b ), the straight lines can begraphically highlighted. The graphically highlighted lines in FIG. 4b )define one of the described components C, D, E, F to be detected, inthis case the crop pickup device 7 in the form of the reel.

Similarly as with the method of velocity characteristic mapdetermination, it is provided in the method of line detection in thisinstance and preferably that the image processing unit 13 groups twoconsecutive images 14, in particular two directly successive images 14,of an image sequence generated by the sensor unit 12 to form an imagepair, and a time interval between the images 14 of the respective imagepair is detected and/or predetermined by the image processing unit 13,and each image 14 of the respective image pair has a line patterncomprising one or more straight lines. The line pattern is a line orlines obtained through the above-described straight line detection. Thisline pattern is highlighted with brightness in FIG. 4b ). In the presentcase, positional displacements of the line patterns between two images14 of a respective image pair which include displacement amounts andparticularly displacement directions of the line patterns can also bedetermined. These displacement amounts and displacement directions canalso be combined for each image pair, respectively, as vectors of avector field of the respective image pair.

It is then possible to calculate velocities, in this embodiment examplethe velocity of a surface portion of a machine part of the crop pickupdevice 7 in the form of the reel, from the displacement amounts of theline patterns between the images 14 of the respective image pair and thetime interval between the images 14 of the respective image pair. Ifanother component C, D, E, F is used instead of the reel as basis forthe method of line detection, the velocities of the surface portions ofthe machine parts of this component C, D, E, F of the crop collectionarrangement 2 can also be determined.

In addition to the detection of the respective component C, D, E, F, inthis instance the reel, and the velocity behavior thereof, the method ofline detection also allows geometric parameters of the respectivecomponent, for example, the inclination and/or height of the component,to be determined simply and quickly.

According to the suggestion, in a particularly preferred configurationit is also possible to analyze certain regions and components A-H fromthose mentioned above relative to one another for determining criteriaand physical parameters.

To this end, the image processing unit 13 can specify one or moreregions A, B, G, H in each instance as reference region and/or one ormore surface portions of machine parts of components C, D, E, F in eachinstance as reference surface portion. The respective reference regionand/or the respective reference surface portion can then be utilized asbasis (reference) for a comparison with another region A, B, G, H and/oranother reference surface portion.

The basic idea in this case is that the actual velocity is known or canbe exactly determined, for example, via speed sensors, for particularregions or surface portions, and this velocity can be utilized tocorrect or to calibrate the velocities calculated on the basis of theimage processing method (e.g., velocity characteristic map determinationand/or line detection). Accordingly, the velocities calculated on thebasis of the image processing methods are always also dependent on theheader adjustments and machine adjustments as well as on environmentalconditions and, therefore, generally vary in each case of use. However,if an actual velocity of a region A, B, G, H or of a surface portion ofa component C, D, E, F is known, a value can also be determined by meansof the latter for the velocity in other regions or surface portions.

For example, the rate of rotation of the reel is generally known so thatthere is also a value for the velocity of the associated surface portionof this component C fixed in the plane of the generated images 14. Thisvelocity or this velocity value forms a reference velocity or areference velocity value. Further, a velocity value of the associatedsurface portion has been calculated with reference to theabove-mentioned displacement amounts. The ratio of the two velocityvalues, i.e., the reference velocity value and the velocity valuecalculated on the basis of the displacement amounts, can now becalculated. Since there is also the same ratio in other regions andsurface portions, the actual velocity for the respective other region orfor the respective other surface portion can be inferred from thevelocity calculated on the basis of the above-mentioned displacementamounts for the respective other region or for the respective othersurface portion.

Accordingly, the image processing unit can be configured to detect acrop pickup device 7, particularly a reel, of the header 2 as acomponent C by means of the method of velocity characteristic mapdetermination and/or by means of the method of line detection and, bymaking use of its actual (known) rate of rotation and comparing thisrate of rotation with the velocity calculated (based on the displacementamounts) for the surface portion of the machine part of component C, todetermine a reference velocity.

The driving speed, which is likewise known, can also be used instead ofthe rate of rotation of the reel, for example. Therefore, there is alsoa value fixed for the velocity of the field stand 5 relative to the cropcollection arrangement 2. Since the field stand 5 is detected in regionsA, B, there is also a value fixed for the velocity in these regions A, Bin the plane of the generated images 14. This velocity or this velocityvalue also forms a reference velocity or a reference velocity value.

Accordingly, the image processing unit can be configured to detect aregion A with the field stand 5 in front of the header 2 or a region Bwith the field stand 5 behind the header 2 by means of the method ofvelocity characteristic map determination and/or by means of the methodof line detection and to determine a reference velocity by making use ofthe actual (known) driving speed of the agricultural work machine 1 andby comparing this driving speed with the velocity which is calculated(based on the displacement amounts) for the field stand 5 of therespective region A, B.

In particular, the image processing unit 13 is configured to calculatethe actual velocity of the crop 4 or field stand 5 in region A, B, D, Hor the actual velocity of the component C, D, E, F in that a velocity ina region A, B, D, H or in a component C, D, E, F, which velocity isdetermined by means of the method of velocity characteristic mapdetermination and/or by means of the method of line detection, iscompared with the reference velocity.

Accordingly, by means of comparing a region A, B, G, H with one or morereference regions or one or more reference surface portions, the imageprocessing unit 13 can determine the produce flow velocity in thisregion. Correspondingly, by comparing a surface portion of a machinepart of a component C, D, E, F with one or more reference regions or oneor more reference surface portions, the image processing unit 13 canalso determine the velocity of the component C, D, E, F having thissurface portion.

REFERENCE CHARACTERS

-   1 agricultural work machine-   2 header, in particular crop collection arrangement-   3 cutting unit-   4 crop-   5 field stand-   6 further work elements-   7 crop pickup device-   8 crop cutting device-   9 crop conveying device-   10 crop intake device-   11 control device-   12 sensor unit-   13 image processing unit-   14 image-   14 a-h image areas-   15 data output unit-   15 a display device-   A-H detected regions and components

What is claimed is:
 1. An agricultural work machine, comprising: aheader for performing agricultural work, and a control device which hasat least one sensor unit configured for detecting a crop stream inand/or around the header and an image processing unit for processingimages which are generated by the sensor unit based on the crop streamdetected via the sensor, wherein the control device is configured todetect regions (A, B, G, H) of like characteristics, components (C, D,E, F) of the header and properties of the crop stream, and is configuredto use that which has been detected for open loop control and/or closedloop control of process sequences in the agricultural work machine,wherein the image processing unit is configured to apply a method ofvelocity characteristic map determination and/or to use a method of linedetection and/or to use at least one color filter for determining theregions (A, B, G, H) and/or components (C, D, E, F) and/or properties ofthe crop stream based on the images generated by the sensor unit, andwherein the image processing unit is configured to carry out an objectdetection by the method of velocity characteristic map determinationand/or the method of line detection, accompanied by the use of at leastone color filter, so that the object detection comprises distinguishingbetween biomass and mechanical objects, and/or wherein the objectdetection comprises distinguishing one or more regions (A, B, G, H) andone or more surface portions of machine parts of the components (C, D,E, F).
 2. The agricultural work machine according to claim 1, whereinthe image processing unit is configured to determine as the region (A) afield stand in front of the header and to identify it as a field standin front of the header, and/or to determine as the region (B) the fieldstand behind the header and to identify it as a field stand behind theheader, and/or to determine as the component (C) a crop pickup device(of the header and to identify it as a crop pickup device, and/or todetermine as the component (D) a crop cutting device of the header andto identify it as crop cutting device, and/or to determine as thecomponent (E) a crop conveying device of the header and to identify itparticularly as crop conveying device, and/or to determine as thecomponent (F) a crop intake device of the header and to identify it as acrop intake device, to determine as the region (G) the crop streaminside of the crop pickup device and to identify it as a crop streaminside of the crop pickup device, and/or to determine as the region (H)the crop stream vertically above the crop cutting device of the header,and to identify it particularly as crop stream vertically above the cropcutting device.
 3. The agricultural work machine according to claim 2,wherein in order to identify a respective determined region (A, B, G, H)or a respective determined component (C, D, E, F), the image processingunit is configured to compare identification data which are associatedwith the respective region (A, B, G, H) or with the respective component(C, D, E, F) and which characterize the respective component and whichare stored in the image processing unit.
 4. The agricultural workmachine according to claim 1, wherein the image processing unit isconfigured to generate a velocity characteristic map which has produceflow velocities and/or velocities of surface portions of machine partsof the components of the header with the method of velocitycharacteristic map determination based on the images generated by thesensor unit.
 5. The agricultural work machine according to claim 1,wherein for producing the velocity characteristic map, the imageprocessing unit is configured to group two consecutive images of animage sequence generated by the sensor unit to form an image pair,wherein a time interval between the images of the respective image pairis detected and/or predetermined by the image processing unit, andwherein each image of the respective image pair has an intensitypattern.
 6. The agricultural work machine according to claim 5, whereinfor producing the velocity characteristic map, the image processing unitis configured to determine positional displacements of the intensitypatterns between the images of the respective image pair, wherein thepositional displacements comprise displacement amounts and displacementdirections of the intensity patterns, so that the displacement amountsand displacement directions for each image pair are combined as vectorsof a vector field of the respective image pair.
 7. The agricultural workmachine according to claim 6, wherein the image processing unit isconfigured to calculate velocities from the displacement amounts of theintensity patterns between the images of the respective image pair andthe time interval between the images of the respective image pair, sothat the velocities are the produce flow velocities of the crop streamand/or the velocities of the surface portions of the machine parts ofthe components of the header.
 8. The agricultural work machine accordingto claim 1, wherein the image processing unit is configured to generatean edge image initially for the respective image in the method of linedetection based on the images generated by the sensor unit and todetermine straight lines in the edge image based on the respective edgeimage.
 9. The agricultural work machine according to claim 8, whereinthe image processing unit is configured to group two consecutive imagesof an image sequence generated by the sensor unit to form an image pairwith the method of line detection, wherein a time interval between theimages of the respective image pair is detected and/or predetermined bythe image processing unit, and wherein each image of the respectiveimage pair has a line pattern comprising one or more straight lines. 10.The agricultural work machine according to claim 9, wherein the imageprocessing unit is configured to determine positional displacements ofthe line patterns between the images of the respective image pair withthe method of line detection, wherein the positional displacementscomprise displacement amounts.
 11. The agricultural work machineaccording to claim 10, wherein the image processing unit is configuredto calculate velocities from the displacement amounts of the linepatterns between the images of the respective image pair and a timeinterval between the images of the respective image pair, wherein thevelocities are velocities of surface portions of the machine parts ofthe components of the header, and/or wherein a velocity is the velocityof a surface portion of a machine part of the crop pickup device. 12.The agricultural work machine according to claim 1, wherein the imageprocessing unit is configured to predetermine one or more regions as areference region, and/or wherein the image processing unit is configuredto predetermine one or more surface portions of machine parts of thecomponents as a reference surface portion.
 13. The agricultural workmachine according to claim 12, wherein the image processing unit isconfigured to use one or more reference regions and/or one or morereference surface portions as basis for a comparison with anotherregion, and/or wherein the image processing unit is configured to useone or more reference regions and/or one or more reference surfaceportions as basis for a comparison with another surface portion of amachine part of a component.
 14. The agricultural work machine accordingto claim 12, wherein the image processing unit is configured todetermine produce flow velocity in a region by comparing the region withone or more reference regions or with one or more reference surfaceportions, and/or the image processing unit is configured, by comparing asurface portion of a machine part of a component with one or morereference regions or one or more reference surface portions, todetermine the velocity of the components having this surface portion.15. The agricultural work machine according to claim 1, wherein theimage processing unit is configured to detect a crop pickup device ofthe header as a component by means of the method of velocitycharacteristic map determination and/or by the method of line detectionand to determine a reference velocity by making use of an actual rate ofrotation of the crop pickup device and by comparing this rate ofrotation with the calculated velocity for the surface portion of themachine part of the component.
 16. The agricultural work machineaccording to claim 15, wherein the image processing unit is configuredto calculate the actual velocity of the crop or field stand in a regionor the actual velocity of a component in that a velocity determined inthe region or in the component by the method of velocity characteristicmap determination and/or by the method of line detection is comparedwith the reference velocity.
 17. The agricultural work machine accordingto claim 1, wherein the image processing unit is configured to detect aregion with a field stand in front of the header or a region with afield stand behind the header by the method of velocity characteristicmap determination and/or by means of the method of line detection and todetermine a reference velocity by making use of the actual driving speedof the agricultural work machine and by comparing this driving speedwith the calculated velocity for the field stand of the respectiveregion.
 18. The agricultural work machine according to claim 1, whereinthe header is a crop collection arrangement for cutting and gatheringcrop from a field stand and has, as components, a crop pickup device, acrop cutting device downstream thereof, a crop conveying devicedownstream thereof and a crop intake device downstream thereof.
 19. Theagricultural work machine according to claim 1, wherein a velocity of asurface portion of a machine part of the respective component isdetermined based on a marker, wherein the marker then forms the surfaceportion that is detected via sensor for determining the velocity of thesurface portion of this component.
 20. Agricultural work machineaccording to claim 1, wherein the sensor unit has at least one opticalsensor in the form of at least one camera and/or at least one Lidarsensor, radar sensor and/or ultrasound sensor for detecting the cropstream and/or the header via sensor.
 21. A method for the operation ofan agricultural work machine having a header for performing agriculturalwork and having a control device which has at least one sensor unit fordetecting a crop stream in and/or around the header and an imageprocessing unit for processing images which are generated by the sensorunit based on the crop stream detected via sensor, comprising detectingwith the control device regions (A, B, G, H) of like characteristics,components (C, D, E, F) of the header and properties of the crop streamand, on the basis thereof, controlling process sequences in theagricultural work machine by open loop controlling and/or closed loopcontrolling, wherein the image processing unit uses a method of velocitycharacteristic map determination and/or uses a method of line detectionand/or uses at least one color filter for determining the regions (A, B,G, H) and/or components (C, D, E, F) and/or properties of the cropstream based on the images generated by the sensor unit, and furthercomprising the step of object detection by the image processing unit, byusing the method of velocity characteristic map determination and/orusing the method of line detection, accompanied by using at least onecolor filter, so that the object detection comprises distinguishingbetween biomass and mechanical objects, and/or wherein the objectdetection comprises distinguishing one or more regions (A, B, G, H) andone or more surface portions of machine parts of the components (C, D,E, F).